The paper introduces CellChat, an open-source tool designed to infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat addresses the limitations of existing methods by considering the complex interactions of ligands, receptors, and cofactors, including heteromeric complexes and soluble factors. The tool uses a curated database of signaling molecule interactions and employs mass action models, differential expression analysis, and statistical tests to predict and visualize intercellular communications. It also provides quantitative analysis through network analysis, pattern recognition, and manifold learning, enabling the identification of key signaling pathways and their roles in cell functions. The authors demonstrate CellChat's effectiveness by applying it to mouse and human skin datasets, showing its ability to extract complex signaling patterns and uncover novel intercellular communications. The tool is available as an R package and a web-based Explorer (http://www.cellchat.org/), facilitating the discovery of novel intercellular communications and the construction of cell-cell communication atlases in diverse tissues.The paper introduces CellChat, an open-source tool designed to infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat addresses the limitations of existing methods by considering the complex interactions of ligands, receptors, and cofactors, including heteromeric complexes and soluble factors. The tool uses a curated database of signaling molecule interactions and employs mass action models, differential expression analysis, and statistical tests to predict and visualize intercellular communications. It also provides quantitative analysis through network analysis, pattern recognition, and manifold learning, enabling the identification of key signaling pathways and their roles in cell functions. The authors demonstrate CellChat's effectiveness by applying it to mouse and human skin datasets, showing its ability to extract complex signaling patterns and uncover novel intercellular communications. The tool is available as an R package and a web-based Explorer (http://www.cellchat.org/), facilitating the discovery of novel intercellular communications and the construction of cell-cell communication atlases in diverse tissues.